An Improved Equilibrium Optimizer Algorithm and Its Application in LSTM Neural Network
An improved equilibrium optimizer (EO) algorithm is proposed in this paper to address premature and slow convergence. Firstly, a highly stochastic chaotic mechanism is adopted to initialize the population for range expansion. Secondly, the capability to conduct global search to jump out of local opt...
Main Authors: | Pu Lan, Kewen Xia, Yongke Pan, Shurui Fan |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-09-01
|
Series: | Symmetry |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-8994/13/9/1706 |
Similar Items
-
Reservoir Prediction Model via the Fusion of Optimized Long Short-Term Memory Network (LSTM) and Bidirectional Random Vector Functional Link (RVFL)
by: Guodong Li, et al.
Published: (2022-10-01) -
An Improved GWO Algorithm Optimized RVFL Model for Oil Layer Prediction
by: Pu Lan, et al.
Published: (2021-12-01) -
TINGKAT KEMIRIPAN DAN KOMPETISI STRUKTUR EKSPOR KOMODITAS REMPAH-REMPAH INDONESIA DI PASAR INTERNASIONAL
by: Herdiana Anggrasari, et al.
Published: (2022-07-01) -
Prediction Model of Ammonia Nitrogen Concentration in Aquaculture Based on Improved AdaBoost and LSTM
by: Yiyang Wang, et al.
Published: (2024-02-01) -
Prediction of Building’s Thermal Performance Using LSTM and MLP Neural Networks
by: Miguel Martínez Comesaña, et al.
Published: (2020-10-01)